Date: Tue, 05 Nov 1996 21:00:33 GMT
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<TITLE> University of Wisconsin - Machine Learning Paper-Reading Group </TITLE>
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     ALT="UW-Madison Machine Learning Research Group" 
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<H3> The Spring '96 paper-reading schedule of the ML research group: </H3>
(Meetings are at 10:00 AM in CS&S 2310, and are open to students who
have taken CS 760 and are willing to present a paper to the group.)
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Our <!WA1><A HREF="http://www.cs.wisc.edu/~shavlik/mlrg//~shavlik/mlrg/old-scheds.html"> old schedules</A> are also on line.
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<UL>
    <LI> March 19 (Tuesday)
       <UL>       
           <LI> <B> J.B. Golden, D. Torgersen, and C. Tibbetts.</B> 1993.
                Pattern Recognition for Automated DNA Sequencing: I. On-line
                Signal Contitioning and Feature Extraction for 
                Basecalling. 
                <EM> First International Conference on Intelligent
                Systems  for Molecular Biology. </EM> 
           <LI> presented by Carolyn Allex
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    <LI> April 2 (Tuesday)
       <UL>       
           <LI> <B> R Miikkilainen, and M. Dyer</B> 1991.<!WA3><a
		href="http://www.cs.utexas.edu/users/nn/abstracts.html#miikkulainen.natural-language.ps.Z">
		Natural Language Processing with Modular Neural Networks and
		Distributed Lexicon. </a>
                <EM> Cognitive Science, Volume 15 pp343-399 </EM> 
                <B>Only read the first 10-15 pages.</B> 
           <LI> presented by Gil
       </UL>
    <BR>
    <LI> April 16 (Tuesday)
       <UL>       
           <LI> <B> J.R. Quinlan</B> 1994.
                Comparing Connectionist and Symbolic Learning Methods
                <EM> Computational Learning Theory and Natural Learning Systems
                I: Constraints and Prospects, </EM> 445-456. Hanson, Drastal,
                and Rivest (eds). Cambridge, MA: MIT Press.
           <li> <b> D.B. Skalak</b> 1994.
                <em> Prototype and Feature Selection by Sampling and Random
                Mutation Hill Climbing Algorithms, </em> 293-301. Proc 11th
                Intl Conf on Machine Learning (ML-94). New Brunswick, NJ:
                Morgan Kaufmann.
           <LI> presented by Kevin Cherkauer
       </UL>
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    <LI> May 14 (Tuesday)
       <UL>       
	<LI> <B> P. Auer, R. Holte and W. Maass</B> 1995.
	<!WA4><A HREF="http://www.csi.uottawa.ca/~holte/Learning/ml95.agnostic-pac.ps">
	Theory and Applications of Agnostic PAC-Learning with Small Decision Trees,
	</A> <EM> Proc. of the 12th International Conference on
	Machine Learning </EM> pp. 21-29.
	<LI> presented by Mark Craven
       </UL>
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